{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "input_collapsed": false
   },
   "outputs": [],
   "source": [
    "from bqplot import *\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "input_collapsed": false
   },
   "outputs": [],
   "source": [
    "price_data1 = [['2015-01-02 00:00:00', [161.31, 163.31, 161.0, 162.06]],\n",
    "              ['2015-01-05 00:00:00', [161.27, 161.27, 159.19, 159.51]],\n",
    "              ['2015-01-06 00:00:00', [159.67, 159.96, 155.17, 156.07]],\n",
    "              ['2015-01-07 00:00:00', [157.2, 157.2, 154.03, 155.05]],\n",
    "              ['2015-01-08 00:00:00', [156.24, 159.044, 155.55, 158.42]],\n",
    "              ['2015-01-09 00:00:00', [158.42, 160.34, 157.25, 159.11]],\n",
    "              ['2015-01-12 00:00:00', [159.0, 159.25, 155.76, 156.44]],\n",
    "              ['2015-01-13 00:00:00', [157.26, 159.97, 155.68, 156.81]],\n",
    "              ['2015-01-14 00:00:00', [154.86, 156.49, 153.74, 155.8]],\n",
    "              ['2015-01-15 00:00:00', [156.69, 156.97, 154.16, 154.57]]]\n",
    "\n",
    "price_data2 = [['2015-01-02 00:00:00', [111.39, 111.44, 107.35, 109.33]],\n",
    "               ['2015-01-05 00:00:00', [108.29, 108.65, 105.41, 106.25]],\n",
    "               ['2015-01-06 00:00:00', [106.54, 107.43, 104.63, 106.26]],\n",
    "               ['2015-01-07 00:00:00', [107.2, 108.2, 106.695, 107.75]],\n",
    "               ['2015-01-08 00:00:00', [109.23, 112.15, 108.7, 111.89]],\n",
    "               ['2015-01-09 00:00:00', [112.67, 113.25, 110.21, 112.01]],\n",
    "               ['2015-01-12 00:00:00', [112.6, 112.63, 108.8, 109.25]],\n",
    "               ['2015-01-13 00:00:00', [111.43, 112.8, 108.91, 110.22]],\n",
    "               ['2015-01-14 00:00:00', [109.04, 110.49, 108.5, 109.8]],\n",
    "               ['2015-01-15 00:00:00', [110.0, 110.06, 106.66, 106.82]]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split up the data into x and y points\n",
    "from bqplot.traits import convert_to_date\n",
    "\n",
    "dates1 = convert_to_date([d[0] for d in price_data1])\n",
    "prices1 = [d[1] for d in price_data1]\n",
    "\n",
    "dates2 = convert_to_date([d[0] for d in price_data2])\n",
    "prices2 = [d[1] for d in price_data2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "input_collapsed": false
   },
   "outputs": [],
   "source": [
    "sc = LinearScale()\n",
    "dt_scale = DateScale()\n",
    "ax_x = Axis(label='X', scale=dt_scale)\n",
    "ax_y = Axis(label='Y', scale=sc, orientation='vertical', tick_format='0.0f')\n",
    "\n",
    "# Construct the marks\n",
    "ohlc = OHLC(x=dates1, y=prices1, marker='candle', scales={'x': dt_scale, 'y': sc}, format='ohlc',\n",
    "            stroke='blue', display_legend=True, labels=['IBM US Equity'])\n",
    "ohlc2 = OHLC(x=dates2, y=prices2, marker='bar', scales={'x': dt_scale, 'y': sc}, colors=['dodgerblue', 'orange'],\n",
    "            stroke='orange', display_legend=True, labels=['AAPL US Equity'], format='ohlc')\n",
    "Figure(axes=[ax_x, ax_y], marks=[ohlc, ohlc2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "input_collapsed": false
   },
   "outputs": [],
   "source": [
    "ohlc.colors = [None, 'red']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "input_collapsed": false
   },
   "outputs": [],
   "source": [
    "sc_y = LinearScale()\n",
    "sc_x = LogScale()\n",
    "\n",
    "ax_x = Axis(label='X', scale=sc_x)\n",
    "ax_y = Axis(label='Y', scale=sc_y, orientation='vertical', tick_format='0.2f')\n",
    "\n",
    "ohlc3 = OHLC(x=np.arange(len(dates2)) + 1, y=np.array(prices2) / 60,\n",
    "             marker='bar', scales={'x': sc_x, 'y': sc_y}, colors=['dodgerblue','orange'])\n",
    "\n",
    "Figure(axes=[ax_x, ax_y], marks=[ohlc3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ohlc3.marker = 'candle'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## OHLC with Ordinal Scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc_x = OrdinalScale()\n",
    "sc_y = LinearScale()\n",
    "\n",
    "ax_x = Axis(label='X', scale=sc_x, tick_format='%d-%m-%Y')\n",
    "ax_y = Axis(label='Y', scale=sc_y, orientation='vertical', tick_format='0.2f')\n",
    "\n",
    "ohlc3 = OHLC(x=dates2, y=np.array(prices2) / 60, marker='candle', \n",
    "             scales={'x': sc_x, 'y': sc_y}, colors=['dodgerblue','orange'])\n",
    "\n",
    "Figure(axes=[ax_x, ax_y], marks=[ohlc3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ohlc3.opacities = [0.1, 0.2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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